Hw 06Untitled

Loading library

library(readxl)
library(tidyverse)

## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr     1.1.4     ✔ readr     2.1.5
## ✔ forcats   1.0.1     ✔ stringr   1.5.2
## ✔ ggplot2   4.0.0     ✔ tibble    3.3.0
## ✔ lubridate 1.9.4     ✔ tidyr     1.3.1
## ✔ purrr     1.1.0     
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag()    masks stats::lag()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors

library(writexl)
library(scales)

## 
## Attaching package: 'scales'
## 
## The following object is masked from 'package:purrr':
## 
##     discard
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## The following object is masked from 'package:readr':
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##     col_factor

summary(1)

##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##       1       1       1       1       1       1

Importing Dataset

bikeshops_tbl <- read_excel("bikeshops.xlsx")
orderlines_tbl <- read_excel("orderlines.xlsx")

## New names:
## • `` -> `...1`

bike_orderlines_tbl <- read_excel("bike_orderlines.xlsx")
summary(2)

##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##       2       2       2       2       2       2

Revenue by category

revenue_by_category2 <- bike_orderlines_tbl %>%
  group_by(category_2) %>%
  summarise(revenue = sum(total_price, na.rm = TRUE)) %>%
  arrange(desc(revenue))
summary (3)

##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##       3       3       3       3       3       3

Plot with ggplot2

ggplot(revenue_by_category2, aes(x = revenue, 
                                 y = reorder(category_2, revenue))) +
  geom_col(fill = "blue") +
  labs(
    x = "revenue",
    y = "category_2",
    title = "Revenue by Bike Subcategory"
  ) +
  scale_x_continuous(labels = label_number()) +  # e.g. 1e+07 → 10M
  theme_minimal()

summary (4)

##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##       4       4       4       4       4       4